Real-time traffic data

Englisch

Real-time traffic data

Data are not validated and are used for demonstration purposes only.

On the Danish web portal OPEN DATA DK there are real-time traffic data from Aarhus Municipality. It is possible to preview data.

Dansk

Realtids trafikdata

Data er ikke valideret og bruges kun til demonstrationsformål.

På den danske web portal OPEN DATA DK findes realtids trafikdata fra Aarhus Kommune. Det er muligt via preview, at undersøger data.
OPEN DATA DK - Real-time traffic data
OPEN DATA DK - Real-time traffic data

There is a link on the page so that you can, using JSON technology, retrieve data from measuring points set up in the municipality of Aarhus. Data is updated every 5 minutes. Using Microsoft Power BI, you can download real-time traffic data and present them. It is possible to examine individual records for the number of vehicles as well as their speed.

På siden findes link, så man ved hjælp af JSON teknologi, kan hente data fra målesteder opsat i Aarhus Kommune. Data bliver opdateret hvert 5. minut. Ved hjælp af Microsoft Power BI, kan man hente realtids trafikdata og præsentere dem. Det er også muligt, at undersøge enkelte strækninger for antal af køretøjer samt deres hastighed.

Microsoft Power BI
Microsoft Power BI

At a web hosting company, you can use a SQL database, PHP technology and set up a cron job to retrieve data continuously 24/7 and create a dataset for further investigation.

Hos et webhosting firma kan man anvende en SQL-database, PHP-teknologi og opsætte et cron job til at hente data kontinuerligt 24/7 og oprette et datasæt til yderligere undersøgelse.

PHP script

After three weeks data collection, the following data sets were constructed with the following fields and 3.168.044 records.

Efter tre ugers dataopsamling blev følgende datasæt opbygget med følgende felter og 3.168.044 poster.

SQL script
Data set

The dataset was loaded into the H2O AI and gradient boosting machine learning algorithm was used to see which input fields correlated with response column = vehicleCount and response column = avgSpeed.

Datasættet blev loaded ind i H2O AI og gradient boosting machine learning algortime blev anvendt for at se, hvilke input felter som korrelerede med response column = vehicleCount og response column = avgSpeed.

H2O AI Flow - response column = vehicleCount
H2O AI Flow - response column = avgSpeed

In both machine learning, correlated input REPORT_NAME fit best in relation to response column = vehicleCount and response column = avgSpeed.

I begge machine learning kørsler korrelerede input REPORT_NAME bedst i forhold til response column = vehicleCount og response column = avgSpeed.

Some REPORT NAME records

REPORT_NAME is a unique road section ID. So we interpret that REPORT_NAME means the same as the accessibility of the road.

REPORT_NAME er et unikt id for en vejstrækning. Så vi tolker at REPORT_NAME betyder det samme som vejens fremkommelighed.